Rag Metrics

RAG metrics are standardized evaluation measures used to assess the performance of Retrieval-Augmented Generation (RAG) systems, which enhance AI language models by retrieving external knowledge to generate more accurate and contextually grounded responses. Essential for developers, researchers, and AI practitioners in the tech community, these metrics—such as retrieval precision, faithfulness, and answer relevance—enable optimization of RAG pipelines for reliable applications in chatbots, search tools, and enterprise knowledge systems.